AI Law and Regulation
This area strongly focuses on the control of AI by means of mechanisms like laws, standards or norms that are already established for different technological applications. Here, there are some challenges special to AI that need to be addressed in the near future, including the governance of autonomous intelligence systems, responsibility and accountability for algorithms as well as privacy and data security.
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit321
Domain lineage
6. Socioeconomic and Environmental
6.5 > Governance failure
Mitigation strategy
1. Implement a comprehensive, risk-based AI governance framework that imposes stringent ex-ante compliance obligations (e.g., risk management systems, quality management, technical documentation) proportionate to the potential impact of autonomous intelligence systems on safety and fundamental rights. 2. Operationalize transparent and traceable accountability mechanisms by design, including mandatory logging and auditable decision trails for all automated outcomes, and establishing defined human-in-the-loop checkpoints or override mechanisms for autonomous agents operating in high-risk environments. 3. Integrate advanced privacy-preserving and cybersecurity-by-design principles throughout the AI system lifecycle, utilizing techniques such as data minimization, pseudonymization, encryption (e.g., homomorphic encryption), and robust access controls to safeguard sensitive data against unauthorized access and adversarial manipulation.